Abstract
Online business-to-business auctions for used IT products have emerged as a viable market for finding a second life for these products, rather than having them end up in landfills as e-waste. As part of the growing “secondary market” landscape, these online B2B auctions are significantly affected by adverse selection since uncertainty about product quality from their first life remains in place. We study how these adverse selection costs may be identified and reduced in online B2B auctions for mobile phones using a proprietary data set for pallets of iPhone devices. We focus on the differences between carrier-locked and unlocked iPhones, and the degree to which the jailbreaking of devices may lead to adverse selection costs. We first show that uncertainty with respect to the possibility of jailbreaking-to-unlock induces significant adverse selection costs in this market. We identify a clear method that these adverse selection costs may be reduced through policies implemented in the primary market. We find that adverse selection costs exist with respect to jailbreaking-to-unlock, by comparing prices obtained for locked and unlocked devices, as well as pallets where this information is not disclosed. However, when some of the uncertainty surrounding jailbreaking-to-unlock is removed by virtue of an exogenous policy change implemented by Verizon in the primary market, i.e., to sell all iPhones as factory unlocked, adverse selection costs are significantly reduced. Our work has significant implications for enhancing the efficiency of secondary markets for IT products, by virtue of highlighting the connections between primary and secondary markets. Managerial and theoretical implications that emerge from this work are discussed in the paper.
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